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Record W2012312025 · doi:10.1117/12.567419

Bias-induced long-term transient in a-Si:H thin film transistors

2004· article· en· W2012312025 on OpenAlexafffund
Shah M. Jahinuzzaman, Peyman Servati, Arokia Nathan

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThin-film transistorMaterials scienceAmorphous siliconTransient (computer programming)TransistorOptoelectronicsThreshold voltageMetastabilityDiodeDangling bondRelaxation (psychology)Amorphous solidOLEDSiliconVoltageCrystalline siliconElectrical engineeringComputer sciencePhysicsNanotechnologyCrystallographyChemistry

Abstract

fetched live from OpenAlex

In this work, we have investigated and modeled an anomalous transient behaviour of the hydrogenated amorphous silicon (a-Si:H) thin film transistor (TFT) in a time scale (of the order of hundreds of seconds) where the threshold voltage shift is not prominent. Such a long term transient in the terminal characteristics can be critical in analog applications of the TFT, such as in pixel driver circuits of organic light emitting diode (OLED) displays. The reproducibility of the transient behaviour regardless of the presence or absence of any thermal annealing cycle suggests that the behaviour is not related to the metastable creation of defects in a-Si:H. The underlying mechanism that we believe is a configurational relaxation of Si dangling bond (D) defects after change in their charge states. Other possible effects including the properties of the source and drain contacts are carefully considered. Based on the defect relaxation mechanism, we have proposed a time dependent drain current model to describe the transient response of the TFT in the forward above threshold regime of operation. The parameters associated with the model are physically based and have strong dependence on the TFT geometry. The measurement data are in good agreement with the simulation results with a discrepancy of less than 5%, thus validating the model.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.221
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2004
Admission routes2
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicThin-Film Transistor TechnologiesFrench-language works237,207